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All Journal Journal of Informatics, Information System, Software Engineering and Applications (INISTA)
Wijaya, Raden Bagus Muhammad AdryanPutra Adhy
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Computer Science & IT

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The Application of LSTM in the AI-Based Enhancement of Classical Compositions Fudholi, Dzikri Rahadian; Putri, Delfia Nur Anrianti; Wijaya, Raden Bagus Muhammad AdryanPutra Adhy; Kusnadi, Jonathan Edmund; Amarissa, Jovinca Claudia
Journal of INISTA Vol 7 No 1 (2024): November 2024
Publisher : LPPM Institut Teknologi Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v7i1.1628

Abstract

Music enhancement through deep learning methodologies presents an innovative approach to refining and augmenting classical compositions. Leveraging a comprehensive dataset of classical piano MIDI files, this study employs LSTM networks with attention mechanisms for music refinement. The model, trained on diverse compositions, demonstrates proficiency in capturing tempo nuances but faces challenges in replicating varied pitch patterns. Assessments by 28 individuals reveal positive reception, particularly in melody integration, scoring notably high at 8 out of 10. However, while praised for cohesion, bass lines received slightly lower scores, suggesting opportunities for enhancing originality and impact. These findings underscore the LSTM model's capability to generate harmonious melodies and highlight refinement areas, particularly in innovating bass lines within classical compositions. This study contributes to advancing automated music refinement, guiding further developments in LSTM-based music generation techniques.
Co-Authors Amarissa, Jovinca Claudia Fudholi, Dzikri Rahadian Kusnadi, Jonathan Edmund Putri, Delfia Nur Anrianti